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chore(release): 2.6.0 [skip ci]
# [2.6.0](v2.5.0...v2.6.0) (2025-11-24) ### Features * Add SWE-bench experiment system for validating AgentReady impact ([#124](#124)) ([15edbba](15edbba))
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CHANGELOG.md

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# [2.6.0](https://github.com/ambient-code/agentready/compare/v2.5.0...v2.6.0) (2025-11-24)
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### Features
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* Add SWE-bench experiment system for validating AgentReady impact ([#124](https://github.com/ambient-code/agentready/issues/124)) ([15edbba](https://github.com/ambient-code/agentready/commit/15edbba94c92bc578ae1445eed7ae1f2f1fe8482))
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# [2.5.0](https://github.com/ambient-code/agentready/compare/v2.4.0...v2.5.0) (2025-11-24)
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CLAUDE.md

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AgentReady is a Python CLI tool that evaluates repositories against 25 carefully researched attributes that make codebases more effective for AI-assisted development. It generates interactive HTML reports, version-control friendly Markdown reports, and machine-readable JSON output.
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**Current Status**: v2.5.0 - Core assessment engine complete, 22/31 attributes implemented (9 stubs), LLM-powered learning, research report management
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**Current Status**: v2.6.0 - Core assessment engine complete, 22/31 attributes implemented (9 stubs), LLM-powered learning, research report management
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**Self-Assessment Score**: 80.0/100 (Gold) - See `examples/self-assessment/`
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**Last Updated**: 2025-11-24 by Jeremy Eder
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**AgentReady Version**: 2.5.0
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**AgentReady Version**: 2.6.0
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**Self-Assessment**: 80.0/100 (Gold) ✨

pyproject.toml

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[project]
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name = "agentready"
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version = "2.5.0"
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version = "2.6.0"
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description = "Assess and bootstrap git repositories for AI-assisted development with automated remediation and continuous learning"
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authors = [{name = "Jeremy Eder", email = "jeder@redhat.com"}]
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readme = "README.md"

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